A Survey on Resource Allocation Schemes in Device-to-Device Communication

Device-to-device (D2D) communication is a breakthrough technology of fifth-generation (5G) and beyond networks. It offers direct communication between D2D devices without communicating via a centralized base station (BS). It works either in an overlay or underlay communication mode. The underlay mode significantly improves spectral efficiency, communication delay, energy efficiency, and overall sum rate. But, it induces huge interference, i.e., inter and intra-cell interferences. To overcome the aforementioned interference issues, researchers across the globe have given various game theory, graph theory, heuristic, deep reinforcement learning (DRL), and machine learning (ML)-based efficient resource management schemes for D2D communication. But, as per the literature explored, there is no such survey that sums up all such solutions and techniques and their comparative analysis. Motivated from this, we present a brief survey on resource allocation schemes, which helps researchers working in this field. We also highlight various open issues and research challenges pertaining to resource allocation in D2D communication.